DataCalc: Ad-hoc Analyses on Heterogeneous Data Sources

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

Abstract

Storing and processing data at different locations using a heterogeneous set of formats and data managements systems is state-of-the-art in many organizations. However, data analyses can often provide better insight when data from several sources is integrated into a combined perspective. In this paper we present an overview of our data integration system DataCalc. DataCalc is an extensible integration platform that executes adhoc analytical queries on a set of heterogeneous data processors. Our novel platform uses an expressive function shipping interface that promotes local computation and reduces data movement between processors. In this paper, we provide a discussion of the overall architecture and the main components of DataCalc. Moreover, we discuss the cost of integrating additional processors and evaluate the overall performance of the platform.

Details

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherIEEE, New York [u. a.]
Pages463-468
Number of pages6
ISBN (electronic)9781728108582
Publication statusPublished - Dec 2019
Peer-reviewedYes

Publication series

Series2019 IEEE International Conference on Big Data (Big Data)

Conference

Title2019 IEEE International Conference on Big Data, Big Data 2019
Duration9 - 12 December 2019
CityLos Angeles
CountryUnited States of America

External IDs

Scopus 85081362423
ORCID /0000-0001-8107-2775/work/142253464